In the field of medical diagnostics and research, pathology, drug discovery and clinical trials, detection, identification, quantification, and characterization of cells of interest, such as cancer cells, is an important aspect of diagnosis and research.
Pathologists use a number of properties in deciding the nature of a cell. Many of these properties do not have a rigid definition and many a times a pathologist provides a pathological decision based on many years of experience. A fundamental aspect of histopathology has been the recognition that the morphological appearance of a tumor can be correlated with a degree of malignancy. In many areas of histopathology, such as a diagnosis of breast carcinoma, does not give enough information for the referring medical clinician to make decisions about patient prognosis and treatment. Therefore manual and automated scoring and grading systems used by pathologists have been developed which provide additional information to medical clinicians. One of these automated scoring and grading systems includes considering mitotic activity of cells.
As is also known in the art, “Mitosis” is a process that facilitates the equal partitioning of replicated chromosomes into two identical groups. Mitosis is a last stage of cell cycle during which cells divide into two cells. In a typical animal cell, mitosis can be divided into four principal stages: (1) “Prophase:” where cell chromatin, diffuse in interphase, condenses into chromosomes. Each chromosome has duplicated and now consists of two sister chromatids. At the end of prophase, the nuclear envelope breaks down into vesicles; (2) “Metaphase:” where the chromosomes align at the equitorial plate and are held in place by microtubules attached to the mitotic spindle and to part of the centromere; (3) “Anaphase:” where the centromeres divide. Sister chromatids separate and move toward the corresponding poles; and (4) Telophase: where the daughter chromosomes arrive at the poles and the microtubules disappear. The condensed chromatin expands and the nuclear envelope reappears. The cytoplasm divides, the cell membrane pinches inward ultimately producing two daughter cells (e.g., “Cytokinesis”).
Several studies have shown that the mitotic count is one of the most important variables in a grading system used for the prognosis of certain cancers including breast cancer. Histological grading has been one of the most important parameters in the determination of the prognosis of breast cancer. One of the important score of cancer grading systems is an evaluation of a Mitotic index of a tissue sample. As is known in the art a “Mitotic index” is an indication of a proliferative activity of a tumor.
Therefore mitotic scoring and grading systems have been developed which provide additional information. A Mitotic Activity Index (“MAI”) is a useful and reproducible prognostic indicator for many cancers including invasive breast cancer. Traditionally, the MAI has been defined as the total number of mitoses counted in ten consecutive high-power fields (e.g., objective, ×40; numeric aperture, 0.75; field diameter, 450 microns), in an area subjectively determined to have most cellular activity at the periphery of the tumor.
There have been attempts to use mitosis prognostic indicator for many cancers. For example, a publication entitled “Mitotic frequency as a prognostic factor in breast cancer” by S. Biesterfeld, I. Noll, E. Noll, D. Wohltmann and A. Bocking, in Human Pathology 26: 47-52 (1995), describes a statistical analysis of prognostic significance of mitosis detection in breast cancer. The objective was to check mitotic grading of tumor malignancy in breast cancer contribute essential information both for the prospective outcome of the individual patient as well as for TNM staging. A series of 104 breast cancer patients were tested the prognostic validity and reproducibility of mitotic figure counting compared with TNM staging, Bloom and Richardson grading, DNA single cell cytometry, and morphometry. Depending on the number of mitotic figures, length of survival was significantly different. With a Cox stepwise regression model mitotic frequency counting was of higher prognostic significance than lymph node status, DNA ploidy, or mean nuclear area.
In another paper entitled “Comparison of the prognostic value of four methods to assess mitotic activity in 186 invasive breast cancer patients: classical and random mitotic activity assessments with correction for volume percentage of epithelium” by I. Jannink, P J van Diest, and J P Baak in Human Pathology 26: 1086-1092(1995) studies are done to check whether the prognostic value of mitotic activity could be improved by a random sampling procedure or correction for percentage of epithelium present. Proliferation markers and especially the Mitotic Activity Index (MAI) are strong and reproducible prognosticators in invasive breast cancer. For this purpose the prognostic value of four methods used to assess mitotic activity in invasive breast cancer was compared in 4-microns-thick hematoxylin-eosin (H&E)-stained sections of 186 primary invasive breast cancer patients. These were the MAI, the random MAI (rMAI), the Mitosis per Volume (M/V) Index, and the random M/V Index (rM/V Index). The rMAI was defined as the total number of mitotic figures counted in 10 random fields through the whole outlined tumor at ×400 magnification. All four methods checked had additional prognostic value to tumor size and lymph node status MAI, however, produced the best results, confirming importance of MAI in prognosis of a carcinoma.
Many pitfalls however, may occur in the determination of the mitotic count which is complex and involved. Mitotic counts differ depending upon the area of tumors analyzed. Margin with the proliferative area give the best results. Mitosis occurs through four successive stages, which are pro-phase, metaphase, anaphase and telophase.
A mitosis score is assessed in the peripheral areas of the neoplasm and not in the sclerotic central zone. The neoplasm is scanned at intermediate magnification to determine the area in which mitoses are most abundant (usually areas of poor tubule formation where cells are arranged in sheets or large nests). Only definite mitotic figures are counted with care to avoid non-mitotic nuclei including pyknotic nuclei in the count.
Grading of some tumors, particularly of the breast, has been done by microscopic examination. In grading breast tumors, pathologists have traditionally used the Scarff-Bloom-Richardson system (see, Le Doussal, V., et al., Cancer 64(9): 1914 (1989)). Although the S-B-R grading of tumors was an attempt at objective quantitation, microscopic tumor grading, by its nature, is subjective. Additionally, to grade tumors, the tumor or the cells from a tumor need to be removed. This requires surgical techniques. Because of the subjective nature of tumor grading, the same pathologist should grade all the tumors. In addition, the pathologist should be well-trained in the grading of tumors by the S-B-R system. Alternatively, two pathologists can be used and the results obtained by each compared for consistency (Robbins, P., et al., Human Pathology. 26(8): 873 (1995)).
Tumors can be graded histopathologically on many different bases. As mentioned above, for malignant breast tumors, grading systems such as S-B-R are preferred because they provide objective values of malignancy grade. The pathologist using the S-B-R system looks to three structural characteristics when grading tumors: (1) nuclear pleomorphism; (2) mitotic index; and (3) the ability of the tumor to form tubular, glandular or capillary formations, i.e., ductoglandular differentiation (see, Le Doussal, supra). Tumors are graded by each criterion separately with 1 being the most normal (differentiated) and 3 the most aberrant (undifferentiated). The scores of the three criteria are added for a final tumor grade. Therefore, the scores can range from 3-5 (well differentiated) to 6-7 (moderately differentiated) and 8-9 (poorly differentiated). Another method is the Nottingham modified criteria of Bloom and Richardson. See Bloom, H. J. G. and Richardson, W. W., Br. J. Cancer 9: 359-377 (1957).
This tumor-grading method was based on histological features of tubule formation, nuclear pleomorphism, and mitotic activity, and points were assigned for each category accordingly. The overall tumor grade was the sum total of scores between 3-9. Tumors with poorly differentiated phenotypes (8-9 points) are likely to have less or no tubular structures, irregular and large nuclei, and high mitotic counts. Tumors with moderately (6-7 points) or well differentiated (3-5 points) phenotypes may have definite tubule formation, moderate outlines of epithelial cell shapes and uniformity of nuclear chromatin, and low mitotic indexes. Mitotic activity is graded as follows as per the Nottingham grading system, how many mitotic figures (all four phases) does the pathologist see in 10 high power (400× magnification) fields. The point score cutoffs depend upon the size of the high power field of the microscope that is used. In general, <5 mitoses per 10 high power fields=1 point, 5-10 mitoses/10 high power fields=2 points, 10 mitoses/10 high power fields=3 points.
Although the Nottingham grading system uses a scoring system based on the number of mitoses per 10 HPF's, the Oncologic Standards Committee considers that a mitotic count per square millimeter is most accurate. Mitoses are only counted in the invasive component of the lesion. Using Clinical Onocological Standards, Mitoses are only counted in an invasive component in a lesion as is illustrated in Table 1.
TABLE 1Score 1:<4mitoses per square mm.Score 2:4-7mitoses per square mm.Score 3:>7mitoses per square mm.
Alternatively the number of mitoses in 10 high power fields (HPFs) is counted. Using an optical microscope with a 40× objective lens (i.e. ×400) and a field surface area of 0.152 mm2, the scores are illustrated in Table 2.
TABLE 2Score 1:0-5mitosesScore 2:6-10mitosesScore 3:>10mitoses
In practice, Contesso's method of scoring of mitoses is quicker and easier to perform especially on small biopsies (e.g., core biopsies). At least twenty high power fields of the same area as stated above are assessed and scored as is illustrated in Table 3.
TABLE 3Score 1:No field contains more than 1 mitosis.Score 2:Two mitoses present in any one HPF.Score 3:Three or more mitoses present in any one HPF.
Other studies have shown mitotic activity index has been shown to be important parameter in medical prognosis. A report by Lynch J, et al., (J Pathol. March 2002; 196(3): 275-9) has shown that use of the mitotic count (MC), which was assessed as part of the grading system, enabled patients to be stratified into “good” and “bad” prognostic groups. Another report by C. Patel et al., (Indian J. Pathol Microbiol. July 2002; 45(3): 247-54.) shows that MAI counted with strict criteria of Elston C W, emerged as one of the most significant prognostic parameter followed by overall grade in predicting Tumor free survival (TFS) for the patients.
Whichever is the system followed, accuracy of the detection of mitotic count is most essential. An overall grade of neoplasm is determined by adding individual score of the three separate parameters, tubules, nuclei and mitoses. The grading of the neoplasm has a very important role to play in the treatment and prognosis of the patient.
However, there are several problems associated using mitosis or a Mitosis index for diagnosing cancer. First, there is a difference in the mitotic counts depending upon the area of tumors analyzed by pathologists. Margins within a proliferative growth area of a tissue sample typically give the best results. However, many tissue samples are not analyzed in a proliferative growth area by pathologists.
Second, Mitosis occurs through four successive stages, which are pro-phase, metaphase, anaphase and telophase. A Mitosis score is typically assessed in peripheral areas of the neoplasm and not in a sclerotic central zone. Thus, the neoplasm is typically scanned at intermediate magnification with an optical microscope to determine an area in which mitoses are most abundant (e.g., usually areas of poor tubule formation where cells are arranged in sheets or large nests). Only definite mitotic figures are counted with care to avoid non-mitotic nuclei including pyknotic nuclei in the count.
It is observed that the seemingly simple task of mitotic cell counting becomes difficult because the counting has to be done for large number of sections. Benign and low grade cancers exhibit less than nine mitotic cells in a ten high power fields of view. Even experienced pathologist might miss genuine mitotic cells due to fatigue. Examination of tissue images typically has been performed manually by either a lab technician or a pathologist. In the manual method, a slide prepared with a biological sample is viewed at a low magnification under an optical microscope to visually locate candidate cells of interest. Those areas of the slide where cells of interest are located are then viewed at a higher magnification to count those objects as cells of interest, such as mitotic cells. In the last few years, slides with stained biological samples are photographed to create digital images from the slides. Digital images are typically obtained using an optical microscope and capturing a digital image of a magnified biological sample.
A digital image typically includes an array, usually a rectangular matrix, of pixels. Each “pixel” is one picture element and is a digital quantity that is a value that represents some property of the image at a location in the array corresponding to a particular location in the image. Typically, in continuous tone black and white images the pixel values represent a “gray scale” value.
Pixel values for a digital image typically conform to a specified range. For example, each array element may be one byte (i.e., eight bits). With one-byte pixels, pixel values range from zero to 255. In a gray scale image a 255 may represent absolute white and zero total black (or visa-versa).
Color images consist of three color planes, generally corresponding to red, green, and blue (RGB). For a particular pixel, there is one value for each of these color planes, (i.e., a value representing the red component, a value representing the green component, and a value representing the blue component). By varying the intensity of these three components, all colors in the color spectrum typically may be created.
However, many images do not have pixel values that make effective use of the full dynamic range of pixel values available on an output device. For example, in the eight-bit or byte case, a particular image may in its digital form only contain pixel values that fall somewhere in the middle of the gray scale range. Similarly, an eight-bit color image may also have RGB values that fall within a range some where in middle of the range available for the output device. The result in either case is that the output is relatively dull in appearance.
The visual appearance of an image can often be improved by remapping the pixel values to take advantage of the full range of possible outputs. That procedure is called “contrast enhancement.” While many two-dimensional images can be viewed with the naked eye for simple analysis, many other two-dimensional images must be carefully examined and analyzed. One of the most commonly examined/analyzed two-dimensional images is acquired using a digital camera connected to an optical microscope.
One type of commonly examined two-dimensional digital images is digital images made from RGB values. Such digital images are commonly used to analyze biological samples including a determination of certain knowledge of medical conditions for humans and animals. For example, digital images are used to determine cell proliferate disorders such as cancers, etc. in humans and animals.
However, there are several problems associated using Mitosis or a Mitosis index for diagnosing cancer. First, there is a difference in the mitotic counts depending upon the area of tumors analyzed by pathologists. Margins within a proliferative growth area of a tissue sample typically give the best results. However, many tissue samples are not analyzed in a proliferative growth area by pathologists. Second, Mitosis occurs through four successive stages, which are pro-phase, metaphase, anaphase and telophase. A mitosis score is typically assessed in peripheral areas of the neoplasm and not in a sclerotic central zone. Thus, the neoplasm is typically scanned at intermediate magnification with an optical microscope to determine an area in which mitoses are most abundant (e.g., usually areas of poor tubule formation where cells are arranged in sheets or large nests). Only definite mitotic figures are counted with care to avoid non-mitotic nuclei including pyknotic nuclei in the count.
There are also several problems associated with using existing digital image analysis techniques for analyzing images for determining mitotic cell count. One problem is that existing digital image analysis uses fluorescent signals to identify mitotic activity. Fluorescent signals are counted to determine the existence of mitotic activity. Since these signals are very small, there is need to image specimen slides at a very high resolution. Once there are a large number of image sections to be processed together, issues like seamless composition of tiles becomes an issue. Further, one needs to prepare a separate slide and capture images through fluorescent microscope.
Another problem is that Haematoxylin and Eosin (H/E) stained tissue used for determining digital saliency can also be used for identification and classification of mitosis. However, using H/E stained tissue with a fluorescent signal based mitosis count typically requires stacking image planes in three dimensions to get a focused image. Otherwise, the small fluorescent signals far below the surface of the tissue will give weak, blurred ring of fluorescent signals. Manual method used is time consuming and prone to error including missing areas of the slide including mitotic cells.
There have been attempts to solve some of the problems associated with automating manual methods for counting mitotic cells. For example, in an article entitled, “Real-Time Image Analysis of Cells Undergoing Mitotic Catastrophe,” by Michael Mackey and Fiorenza lanzini of University of Iowa describe experiments to determine the fate of cells undergoing mitotic catastrophe following radiation exposure using the Large Scale Digital Cell Analysis System (LSDCAS) at Real-Time Cell Analysis Facility. LSDCAS is a computer-controlled microscope system that is capable of automatically generating digital movies of over 1000 separate microscope fields over a three-week interval following treatment.
IMSTAR S. A., a French-based, company designs, manufactures and markets automated digital imaging systems for Life Sciences Research and Clinical departments in Cytogenetics, Pathology, Cytology, Functional genomic, Drug Development and Validation. IMSTAR launched PATHFINDER™ automated, and cost effective Image Cytometer, associated with a number of Application Software Analysis modules to facilitate and speed up research and diagnostics. This system provides detection of cell proliferation within breast cancer cells.
CompuCyte Corporation, of Cambridge, Mass. has a product for Cell Cycle and DNA Content Analysis. The total amount of DNA per cell is stoichiometrically determined to obtain cell cycle distributions. In addition, one of the morphometric features obtained for segmented nuclei, analysis, is directly correlated with condensation of chromatin in nuclei and can be used to differentiate interphase cells from mitotic cells.
U.S. Pat. No. 6,605,432, entitled “High-throughput methods for detecting DNA methylation,” that issued to Tim Hui-Ming Huang teaches “a method of method of hybridization, differential methylation hybridization (DMH) for high throughput methylation analysis of multiple CpG island loci. DMH utilizes nucleic acid probes prepared from a cell sample to screen numerous CpG dinucleotide rich fragments affixed on a screening array. Positive hybridization signals indicate the presence of methylated sites. Methods of preparing the hybridization probes and screening array are also provided.”
U.S. Pat. No. 6,009,342, entitled “Imaging method for the grading of tumors,” that issued to Brasch, et al. teaches “the endothelial integrity of microvessels is disturbed in malignant tumors. MRIs are used to define tumor microvascular permeabilities and correlated the permeabilities with histologic grade in tumors. Using macromolecular MRI contrast medium, tumor microvascular permeability values were discovered to be significantly lower in benign tumors than in carcinomas. In addition, the microvascular permeability values demonstrated a strong correlation with the histologic grade of carcinomas as determined by the Scarff-Bloom-Richardson grading system.”
In U.S. Pat. No. 4,724,543, entitled “Method and apparatus for automatic digital image analysis,” that issued to Robert R. Klevecz, et al. teaches a “method and apparatus for digitally analyzing continuous visual images, particularly with reference to the detection of mammalian cell mitotic events is disclosed. The visual images are analyzed by first extracting high frequency picture components, threshold comparison of such components and probing for annular objects indicative of putative mitotic cells. The detection of annulae is performed by an algorithm for recognizing rings of differential radii and compensating for other variations. Thereafter, spatial and temporal relationships between such objects is stored and compared to determine whether cell division occurred.”
In U.S. patent application No. 20030092047, entitled “Methods of cytodiagnostic staging of neoplasia and squamous cell carcinoma,” published by Vickie J. LaMorte et al. describes “Methods of diagnosing whether an epithelial tissue is an abnormal tissue by determining an expression pattern for PML in the epithelial tissue; determining an expression pattern for nuclear bodies in the epithelial tissue; determining SUMO-1 colocalization and comparing the expression pattern for PML and the expression pattern for nuclear bodies with a control are disclosed. Also disclosed are methods for diagnosing whether a subject has mild dysplasia, moderate dysplasia, Type A severe dysplasia, Type B severe dysplasia, cervical squamous cell carcinoma, or poorly-differentiated cervical squamous cell carcinoma by determining an expression pattern for PML in an epithelial tissue sample from the subject; determining an expression pattern for nuclear bodies in the epithelial tissue; determining SUMO-1 colocalization; and determining whether the expression pattern for PML, the expression pattern for nuclear bodies, and the SUMO-1 colocalization of the epithelial tissue sample is consistent with expression patterns expected for mild dysplasia, moderate dysplasia, Type A severe dysplasia, Type B severe dysplasia, cervical squamous cell carcinoma, or poorly-differentiated cervical squamous cell carcinoma.”
In U.S. patent application No. 20030049701, entitled “Oncology tissue microarrays” published by Patrick J. Muraca, discloses “the invention provides oncology tissue microarrays. In one aspect, the microarrays comprise a plurality of cell and/or tissue samples, each sample representing a different type of cancer. In another aspect of the invention, each sample represents a different stage of cancer. In still a further aspect of the invention, samples are ordered on the substrate of the microarray into groups according to common characteristics of the patients from whom the samples are obtained. By dividing tissue samples on the substrate into different groupings representing different tissue types, subtypes, histological lesions, and clinical subgroups, the microarrays according to the invention enable ultra-high-throughput molecular profiling.”
However, these attempts still do not solve all of the problems associated with analyzing a digital image of stained tissue for identification and classification of mitosis for medical diagnosis and prognosis. Thus, it is desirable to provide an automated mitosis identification and classification image analysis system.